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Showing papers in "Wiley Interdisciplinary Reviews: Computational Molecular Science in 2014"


Journal ArticleDOI
TL;DR: The main capabilities of cp2k are summarized, and with recent applications the science cp2K has enabled in the field of atomistic simulation are illustrated.
Abstract: cp2k has become a versatile open-source tool for the simulation of complex systems on the nanometer scale. It allows for sampling and exploring potential energy surfaces that can be computed using a variety of empirical and first principles models. Excellent performance for electronic structure calculations is achieved using novel algorithms implemented for modern and massively parallel hardware. This review briefly summarizes the main capabilities and illustrates with recent applications the science cp2k has enabled in the field of atomistic simulation.

2,114 citations


Journal ArticleDOI
Kestutis Aidas1, Celestino Angeli2, Keld L. Bak3, Vebjørn Bakken4, Radovan Bast5, Linus Boman6, Ove Christiansen3, Renzo Cimiraglia2, Sonja Coriani7, Pål Dahle8, Erik K. Dalskov, Ulf Ekström4, Thomas Enevoldsen9, Janus J. Eriksen3, Patrick Ettenhuber3, Berta Fernández10, Lara Ferrighi, Heike Fliegl4, Luca Frediani, Kasper Hald11, Asger Halkier, Christof Hättig12, Hanne Heiberg13, Trygve Helgaker4, Alf C. Hennum14, Hinne Hettema15, Eirik Hjertenæs16, Stine Høst3, Ida-Marie Høyvik3, Maria Francesca Iozzi17, Brannislav Jansik18, Hans-Jørgen Aa. Jensen9, Dan Jonsson, Poul Jørgensen3, Johanna Kauczor19, Sheela Kirpekar, Thomas Kjærgaard3, Wim Klopper20, Stefan Knecht21, Rika Kobayashi22, Henrik Koch16, Jacob Kongsted9, Andreas Krapp, Kasper Kristensen3, Andrea Ligabue23, Ola B. Lutnæs24, Juan Ignacio Melo25, Kurt V. Mikkelsen26, Rolf H. Myhre16, Christian Neiss27, Christian B. Nielsen, Patrick Norman19, Jeppe Olsen3, Jógvan Magnus Haugaard Olsen9, Anders Osted, Martin J. Packer9, Filip Pawłowski28, Thomas Bondo Pedersen4, Patricio Federico Provasi29, Simen Reine4, Zilvinas Rinkevicius5, Torgeir A. Ruden, Kenneth Ruud, Vladimir V. Rybkin20, Paweł Sałek, Claire C. M. Samson20, Alfredo Sánchez de Merás30, Trond Saue31, Stephan P. A. Sauer26, Bernd Schimmelpfennig20, Kristian Sneskov11, Arnfinn Hykkerud Steindal, Kristian O. Sylvester-Hvid, Peter R. Taylor32, Andrew M. Teale33, Erik I. Tellgren4, David P. Tew34, Andreas J. Thorvaldsen3, Lea Thøgersen35, Olav Vahtras5, Mark A. Watson36, David J. D. Wilson37, Marcin Ziółkowski38, Hans Ågren5 
TL;DR: Dalton is a powerful general‐purpose program system for the study of molecular electronic structure at the Hartree–Fock, Kohn–Sham, multiconfigurational self‐consistent‐field, Møller–Plesset, configuration‐interaction, and coupled‐cluster levels of theory.
Abstract: Dalton is a powerful general-purpose program system for the study of molecular electronic structure at the Hartree-Fock, Kohn-Sham, multiconfigurational self-consistent-field, MOller-Plesset, confi ...

1,212 citations


Journal ArticleDOI
TL;DR: An overview of some of the more popular CG models used in biomolecular applications to date, focusing on models that retain chemical specificity, are provided.
Abstract: Computational modeling of biological systems is challenging because of the multitude of spatial and temporal scales involved. Replacing atomistic detail with lower resolution, coarse grained (CG), beads has opened the way to simulate large-scale biomolecular processes on time scales inaccessible to all-atom models. We provide an overview of some of the more popular CG models used in biomolecular applications to date, focusing on models that retain chemical specificity. A few state-of-the-art examples of protein folding, membrane protein gating and self-assembly, DNA hybridization, and modeling of carbohydrate fibers are used to illustrate the power and diversity of current CG modeling.

464 citations


Journal ArticleDOI
TL;DR: Newton‐X can perform nonadiabatic dynamics using Columbus, Turbomole, Gaussian, and Gamess program packages with multireference configuration interaction, multiconfigurational self‐consistent field, time‐dependent density functional theory, and other methods.
Abstract: The Newton-X program is a general-purpose program package for excited-state molecular dynamics, including nonadiabatic methods. Its modular design allows Newton-X to be easily linked to any quantum-chemistry package that can provide excited-state energy gradients. At the current version, Newton-X can perform nonadiabatic dynamics using Columbus, Turbomole, Gaussian, and Gamess program packages with multireference configuration interaction, multiconfigurational self-consistent field, time-dependent density functional theory, and other methods. Nonadiabatic dynamics simulations with a hybrid combination of methods, such as Quantum-Mechanics/Molecular-Mechanics, are also possible. Moreover, Newton-X can be used for the simulation of absorption and emission spectra. The code is distributed free of charge for noncommercial and nonprofit uses at www.newtonx.org. WIREs Comput Mol Sci 2014, 4:26–33. doi: 10.1002/wcms.1158 The authors have declared no conflicts of interest in relation to this article. For further resources related to this article, please visit the WIREs website.

383 citations


Journal ArticleDOI
TL;DR: A number of options including parallel execution based on the message‐passing capabilities of the interfaced packages and task‐farming for applications in which a number of individual QM, MM, or QM/MM calculations can performed simultaneously are described.
Abstract: ChemShell is a modular computational chemistry package with a particular focus on hybrid quantum mechanical/molecular mechanical (QM/MM) simulations. A core set of chemical data handling modules and scripted interfaces to a large number of quantum chemistry and molecular modeling packages underpin a flexible QM/MM scheme. ChemShell has been used in the study of small molecules, molecular crystals, biological macromolecules such as enzymes, framework materials including zeolites, ionic solids, and surfaces. We outline the range of QM/MM coupling schemes and supporting functions for system setup, geometry optimization, and transition-state location (including those from the open-source DL-FIND optimization library). We discuss recently implemented features allowing a more efficient treatment of long range electrostatic interactions, X-ray based quantum refinement of crystal structures, free energy methods, and excited-state calculations. ChemShell has been ported to a range of parallel computers and we describe a number of options including parallel execution based on the message-passing capabilities of the interfaced packages and task-farming for applications in which a number of individual QM, MM, or QM/MM calculations can performed simultaneously. We exemplify each of the features by brief reference to published applications.

357 citations


Journal ArticleDOI
TL;DR: This discussion is methods‐based and focused on some algorithms that chemoinformatics researchers frequently use, particularly relevant approaches include Artificial Neural Networks, Random Forest, Support Vector Machine, k‐Nearest Neighbors and naïve Bayes classifiers.
Abstract: Machine learning algorithms are generally developed in computer science or adjacent disciplines and find their way into chemical modeling by a process of diffusion. Though particular machine learning methods are popular in chemoinformatics and quantitative structure–activity relationships (QSAR), many others exist in the technical literature. This discussion is methods-based and focused on some algorithms that chemoinformatics researchers frequently use. It makes no claim to be exhaustive. We concentrate on methods for supervised learning, predicting the unknown property values of a test set of instances, usually molecules, based on the known values for a training set. Particularly relevant approaches include Artificial Neural Networks, Random Forest, Support Vector Machine, k-Nearest Neighbors and naive Bayes classifiers. WIREs Comput Mol Sci 2014, 4:468–481. How to cite this article: WIREs Comput Mol Sci 2014, 4:468–481. doi:10.1002/wcms.1183

346 citations


Journal ArticleDOI
TL;DR: Subsystem density functional theory (subsystem DFT) as mentioned in this paper is a powerful alternative to Kohn-Sham DFT for quantum chemical calculations of complex systems, which exploits the idea of representing the total electron density as a sum of subsystem densities.
Abstract: Subsystem density-functional theory (subsystem DFT) has developed into a powerful alternative to Kohn–Sham DFT for quantum chemical calculations of complex systems. It exploits the idea of representing the total electron density as a sum of subsystem densities. The optimum total density is found by minimizing the total energy with respect to each of the subsystem densities, which breaks down the electronic-structure problem into effective subsystem problems. This enables calculations on large molecular aggregates and even (bio-)polymers without system-specific parameterizations. We provide a concise review of the underlying theory, typical approximations, and embedding approaches related to subsystem DFT such as frozen-density embedding (FDE). Moreover, we discuss extensions and applications of subsystem DFT and FDE to molecular property calculations, excited states, and wave function in DFT embedding methods. Furthermore, we outline recent developments for reconstruction techniques of embedding potentials arising in subsystem DFT, and for using subsystem DFT to incorporate constraints into DFT calculations. For further resources related to this article, please visit the WIREs website.

314 citations


Journal ArticleDOI
TL;DR: Double-hybrid density functionals (DHDFs) are reviewed in this paper, where the contribution of nonlocal Fock-exchange and second-order perturbative correlation is replaced by contributions from nonlocal perturbation correlation.
Abstract: Double-hybrid density functionals (DHDFs) are reviewed in this study. In DHDFs parts of conventional density functional theory (DFT) exchange and correlation are replaced by contributions from nonlocal Fock-exchange and second-order perturbative correlation. The latter portion is based on the well-known MP2 wave-function approach in which, however, Kohn–Sham orbitals are used to calculate its contribution. First, related methods preceding this idea are reviewed, followed by a thorough discussion of the first modern double-hybrid B2-PLYP. Parallels and differences between B2-PLYP and its various successors are then outlined. This discussion is rounded off with representative thermochemical examples demonstrating that DHDFs belong to the most robust and accurate DFT approaches currently available. This analysis also presents hitherto unpublished results for recently developed DHDFs. Finally, how double-hybrids can be combined with linear-response time-dependent DFT is also outlined and the value of this approach for electronically excited states is shown. WIREs Comput Mol Sci 2014, 4:576–600. doi: 10.1002/wcms.1193 For further resources related to this article, please visit the WIREs website. Conflict of interest: The authors have declared no conflicts of interest for this article.

280 citations


Journal ArticleDOI
Walter Thiel1
TL;DR: The semi-empirical methods of quantum chemistry are reviewed, with emphasis on established neglect of diatomic differential overlap-based methods (MNDO, AM1, PM3) and on the more recent orthogonalization-corrected methods (OM1, OM2, OM3) as discussed by the authors.
Abstract: The semiempirical methods of quantum chemistry are reviewed, with emphasis on established neglect of diatomic differential overlap-based methods (MNDO, AM1, PM3) and on the more recent orthogonalization-corrected methods (OM1, OM2, OM3). After a brief historical overview, the methodology is presented in nontechnical terms, covering the underlying concepts, parameterization strategies, and computational aspects, as well as linear scaling and hybrid approaches. The application section addresses selected recent benchmarks and surveys ground-state and excited-state studies, including recent OM2-based excited-state dynamics investigations.

240 citations


Journal ArticleDOI
TL;DR: In this paper, general rules that govern multistep reactions of the total electronic spin of the reacting system are discussed, and a particularly strong focus is given to general rules governing multi-step reactions of this type.
Abstract: Many chemical reactions involve one or more changes in the total electronic spin of the reacting system as part of one or more elementary steps. Computational and theoretical methods that can be used to understand such reaction steps are described, and a number of recent examples are highlighted. A particularly strong focus is given to general rules that govern multistep reactions of this type. The two most important rules are (1) that spin-state change without change in atom connectivity, or spin crossover, is facile and rapid, at least when it is exothermic; and (2) that reactions involving spin-state change and changes in atom connectivity tend to prefer stepwise mechanisms in which spin crossover steps alternate with spin-allowed bond-making and breaking steps. WIREs Comput Mol Sci 2014, 4:1–14. doi: 10.1002/wcms.1154 The authors have declared no conflicts of interest in relation to this article. For further resources related to this article, please visit the WIREs website.

184 citations


Journal ArticleDOI
TL;DR: Density functional theory functionals with a high amount of exact exchange are fast and reliable methods for halogen bonds, but double hybrids are more robust if other types of interactions are involved.
Abstract: Halogen bonds, the formally noncovalent interactions where the halogen acts as a Lewis acid, have brought several controversies to the theoretical world regarding its nature and components, e.g., charge transfer (CT), electrostatics, dispersion, and polarization. The debate on whether all characteristics are accounted for by electrostatics is examined, highlighting the importance of the CT and repulsive interactions. A number of strongly halogen-bonded complexes are as covalent as metal–ligand coordination bonds. Different levels of computational methods are reviewed with the objective of finding the best accuracy/cost ratios. The unusual electronic anisotropy of the halogen donor and its interaction with a Lewis base demand specific calculation schemes. From the wave-function theory methods, only the ones with empirical corrections (spin-component-scaled MP2 or CCSD, and MP2.5) are suitable when CCSD(T) is unattainable. Density functional theory functionals with a high amount of exact exchange are fast and reliable methods for halogen bonds, but double hybrids are more robust if other types of interactions are involved. Molecular mechanics methods can be useful, but only when specific corrections are added to compensate for the inability of such methods to describe CT. The most common method introduces a virtual site with a partial positive charge to account for the quantum chemical effect of the halogen bond. This methodology has been successfully applied to study protein–ligand interactions for drug design. WIREs Comput Mol Sci 2014, 4:523–540. doi: 10.1002/wcms.1189 Conflict of interest: The authors have declared no conflicts of interest for this article. For further resources related to this article, please visit the WIREs website.

Journal ArticleDOI
TL;DR: In this article, the authors review recent extensions of the density functional tight binding (DFTB) methodology and its application to organic and biological molecules and discuss the extension to third order, DFTB3, which in combination with a modification of the Coulomb interactions in the second-order formalism and a new parametrization scheme leads to a significant improvement of the overall performance.
Abstract: In this work, we review recent extensions of the density functional tight binding (DFTB) methodology and its application to organic and biological molecules. DFTB denotes a class of computational models derived from density functional theory (DFT) using a Taylor expansion around a reference density. The first- and second-order models, DFTB1 and DFTB2, have been reviewed recently (WIREs Comput Mol Sci 2012, 2:456–465). Here, we discuss the extension to third order, DFTB3, which in combination with a modification of the Coulomb interactions in the second-order formalism and a new parametrization scheme leads to a significant improvement of the overall performance. The performance of DFTB2 and DFTB3 for organic and biological molecules are discussed in detail, as well as problems and limitations of the underlying approximations. WIREs Comput Mol Sci 2014, 4:49–61. doi: 10.1002/wcms.1156 The authors have declared no conflicts of interest in relation to this article. For further resources related to this article, please visit the WIREs website.

Journal ArticleDOI
TL;DR: In this paper, the combination of symmetry-adapted perturbation theory (SAPT) of intermolecular interactions with a density functional theory (DFT) description of the underlying molecular properties is reviewed, with a focus on methodology.
Abstract: The combination of symmetry-adapted perturbation theory (SAPT) of intermolecular interactions with a density functional theory (DFT) description of the underlying molecular properties, known as DFT-SAPT or SAPT(DFT), is reviewed, with a focus on methodology. A theoretical formalism avoiding an overlap expansion and the single-exchange approximation for the second-order exchange contributions is presented, and ways to include higher order contributions are discussed. The influence of the exchange-correlation potential and kernel underlying any DFT-SAPT calculation will be explicated. Enhancements of the computational efficiency through density fitting are described and comparisons to coupled cluster theory and experiment benchmark the performance of the method.

Journal ArticleDOI
TL;DR: How far free‐energy calculations have come, what are the current hurdles they have to overcome, and the challenges they are facing for tomorrow are discussed.
Abstract: In a matter of three decades, free-energy calculations have emerged as an indispensable tool to tackle deep biological questions that experiment alone has left unresolved. In spite of recent advances on the hardware front that have pushed back the limitations of brute-force molecular dynamics simulations, opening the way to time and size scales hitherto never attained, they represent a cogent alternative to access with unparalleled accuracy the thermodynamics and possibly the kinetics that underlie the complex processes of the cell machinery. From a pragmatic perspective, the present review draws a picture of how the field has been shaped and invigorated by milestone developments, application, and sometimes rediscovery of foundational principles laid down years ago to reach new frontiers in the exploration of intricate biological phenomena. Through a series of illustrative examples, distinguishing between alchemical and geometrical transformations, it discusses how far free-energy calculations have come, what are the current hurdles they have to overcome, and the challenges they are facing for tomorrow. WIREs Comput Mol Sci 2014, 4:71–89. doi: 10.1002/wcms.1157 The author has declared no conflicts of interest in relation to this article. For further resources related to this article, please visit the WIREs website.

Journal ArticleDOI
TL;DR: In this article, the authors present a survey of the development of ab initio molecular dynamics (AIMD), where finite-temperature dynamical trajectories are generated using interatomic forces which are calculated on the fly using accurate electronic structure calculations.
Abstract: Computer simulation methods, such as Monte Carlo or molecular dynamics, are very powerful theoretical techniques to provide detailed and essentially exact informations on rather complex classical many-body problems. With the advent of ab initio molecular dynamics (AIMD), where finite-temperature dynamical trajectories are generated using interatomic forces which are calculated on the fly using accurate electronic structure calculations, the scope of computational research has been greatly extended. This review is intended to outline the basic principles as well as being a survey of the field. Beginning with the derivation of Born–Oppenheimer molecular dynamics, the Car–Parrinello method and the recently devised Car–Parrinello-like approach to Born–Oppenheimer molecular dynamics, which unifies the best of both schemes are discussed. The predictive power of the latter second-generation Car–Parrinello molecular dynamics approach is demonstrated by several applications ranging from liquid metals to semiconductors and water. This development allows for ab initio simulations on much larger length and timescales than previously thought feasible. For further resources related to this article, please visit the WIREs website.

Journal ArticleDOI
TL;DR: Long-range correction for exchange functionals in Kohn-Sham density functional theory and its applicability are reviewed in this article, where valence occupied and unoccupied orbital energies are quantitatively reproduced in a comprehensive manner.
Abstract: Long-range correction for exchange functionals in Kohn–Sham density functional theory and its applicability are reviewed. Long-range correction simply supplements the long-range exchange effect in exchange functionals by replacing the Hartree–Fock exchange integral with the long-range part of exchange functionals. Nevertheless, this correction has solved many problems in Kohn–Sham calculations. Using this correction, valence occupied and unoccupied orbital energies are quantitatively reproduced in a comprehensive manner for the first time. Long-range correction has also solved the underestimations of charge transfer excitation energies and oscillator strengths in time-dependent Kohn–Sham calculations and has clearly improved poor optical response properties such as hyperpolarizability in coupled-perturbed Kohn–Sham and finite-field calculations. Moreover, this correction has drastically improved the reproducibility of van der Waals bonds by simply combining with conventional van der Waals calculation methods. We, therefore, believe that the long-range correction clearly extends the applicability of the Kohn–Sham method in future quantum chemistry calculations. For further resources related to this article, please visit the WIREs website.

Journal ArticleDOI
TL;DR: In this paper, different methods to calculate tunneling rates are presented, ranging from full solutions of the time-dependent Schrodinger equation via the semiclassical method to ad hoc corrections of classical transition state theory.
Abstract: Quantum tunneling of atoms, the penetration of energy barriers higher than the total energy of the system, plays a role in many chemical systems. While any chemical reaction is dominated by tunneling at low enough temperature, there is evidence for hydrogen atom tunneling even in enzymatic reactions at ambient conditions. The smaller the mass of the atoms, the lower and thinner the barrier is, the stronger the tunneling effect increases the reaction rate. Different methods to calculate tunneling rates are available. They range from full solutions of the time-dependent Schrodinger equation via the semiclassical method to ad hoc corrections of classical transition state theory. The basis of different methods, their accuracy, and applicability is discussed in the present overview, with a particular focus on instanton theory, a Feynman-path-based approach using the semiclassical approximation.

Journal ArticleDOI
TL;DR: In the 1990s, time-dependent density functional theory (TDDFT) became available for routine calculations and was used to calculate the electronic states of long oligomers as mentioned in this paper.
Abstract: Conducting organic polymers (COPs) became an active field of research after it was discovered how thin films rather than insoluble infusible powders can be produced. The combination of the properties of plastics with those of semiconductors opened the research field of organic electronics. COPs share many electronic properties with inorganic semiconductors, but there are also major differences, e.g., the nature of the charge carriers and the amount of the exciton binding energy. Theoretical analysis has been used to interpret experimental observations early on. The polaron model that was developed from one-electron theories is still the most widely used concept. In the 1990s, time-dependent density functional theory (TDDFT) became available for routine calculations. Using TDDFT, electronic states of long oligomers can be calculated. Now UV spectra of neutral and oxidized or reduced species can be compared with in situ UV spectra recorded during doping. Likewise states of cations can be used to model photoelectron spectra. Analysis of states has resolved several puzzles which cannot be understood with the polaron model, e.g., the origin of the dual absorption band of green polymers and the origin of a ‘vestigial neutral band’ upon doping of long oligomers. DFT calculations also established that defect localization is not crucial for spectral changes observed during doping and that there are no bound bipolarons in COPs. © 2014 John Wiley & Sons, Ltd.

Journal ArticleDOI
TL;DR: The progress that has been made in the study of coupled folding and binding using molecular dynamics simulation is examined, and what has been learnt is summarized and the state of the art is examined in terms of both methodologies and models.
Abstract: Intrinsically disordered proteins (IDPs) are a class of protein that, in the native state, possess no well-defined secondary or tertiary structure, existing instead as dynamic ensembles of conformations They are biologically important, with approximately 20% of all eukaryotic proteins disordered, and found at the heart of many biochemical networks To fulfil their biological roles, many IDPs need to bind to proteins and/or nucleic acids And although unstructured in solution, IDPs typically fold into a well-defined three-dimensional structure upon interaction with a binding partner The flexibility and structural diversity inherent to IDPs makes this coupled folding and binding difficult to study at atomic resolution by experiment alone, and computer simulation currently offers perhaps the best opportunity to understand this process But simulation of coupled folding and binding is itself extremely challenging; these molecules are large and highly flexible, and their binding partners, such as DNA or cyclins, are also often large Therefore, their study requires either simplified representations, advanced enhanced sampling schemes, or both It is not always clear that existing simulation techniques, optimized for studying folded proteins, are well suited to IDPs In this article, we examine the progress that has been made in the study of coupled folding and binding using molecular dynamics simulation We summarize what has been learnt, and examine the state of the art in terms of both methodologies and models We also consider the lessons to be learnt from advances in other areas of simulation and highlight the issues that remain of be addressed

Journal ArticleDOI
TL;DR: In this paper, the Lagrangian formulation was used for general derivative theory and applied to nuclear coordinates with respect to electric and magnetic perturbations, which is a better alternative than using the Hellmann-Feynman theorem with an extended basis set.
Abstract: Analytical calculation of energy derivatives with respect to nuclear coordinates revolutionized applied molecular quantum mechanics by allowing the routine calculation of molecular structures and related properties. The cost of calculating first derivatives (gradients, forces) is comparable to the calculation of the energy for most electronic structure methods. Thus analytical differentiation, compared to numerical one, increases efficiency by a factor proportional to the number of nuclei and greatly improves numerical accuracy. Coordinate derivatives, together with their generalizations to electric and magnetic perturbations, are crucial for the determination of transition states, vibrational frequencies, infrared and Raman intensities, non-Born–Oppenheimer couplings, and magnetic properties: NMR spectra, magnetizability, vibrational circular dichroism, etc. Derivative theory, unlike perturbation theory, generally requires perturbation-dependent basis sets. The inclusion of contributions originating from this dependence is a better alternative than using the Hellmann–Feynman theorem with an extended basis set. Analytical second derivatives, compared to the numerical differentiation of first derivatives, do not yield savings similar to first derivatives versus energy, in accordance with Wigner's 2n + 1 rule, but still improve greatly efficiency and numerical accuracy. Third and fourth derivatives have also been implemented for simpler wavefunctions. Analytical gradients were initially formulated for variational wavefunctions. It was realized only later that the penalty for nonvariational wavefunctions is modest. The Lagrangian formulation provides a simple, elegant framework for general derivative theory. Disadvantages of analytical derivatives are increased code complexity, and, particularly for higher derivatives, the requirement of large blocks of computer time and memory, both of which may interfere with code parallelization.

Journal ArticleDOI
TL;DR: A review of the recent and exciting work in this area and an overview of popular strategies for generating reliable properties and benchmark quality energetics for water clusters with correlated wavefunction methods can be found in this paper.
Abstract: Although the first ab initio Hartree–Fock computations of the water dimer were reported more than four decades ago, the detailed characterization of water clusters with sophisticated electronic structure techniques remains an important and vibrant area of research. The field of computational quantum chemistry has made significant advances since those pioneering studies. Geometry optimizations of the water dimer can now be carried out at the CCSDTQ level, and CCSD(T) energies can be computed with the aug-cc-pVTZ basis for clusters as large as (H2O)17. Some of these high-level studies are starting to reveal that the electronic structure is harder to describe for some hydrogen bonds than others. For example, discrepancies between MP2 and CCSD(T) energetics tend to increase when there are qualitative differences in the hydrogen-bonding networks of the water clusters being studied. This review highlights the recent and exciting work in this area and provides an overview of popular strategies for generating reliable properties and benchmark quality energetics for water clusters with correlated wavefunction methods.

Journal ArticleDOI
TL;DR: In this article, a general 1-component normalized elimination of the small component (NESC) algorithm is presented for the calculation of reliable energies, geometries, electron density distributions, electric moments, electric field gradients, hyperfine structure constants, contact densities and Mossbauer isomer shifts.
Abstract: Dirac-exact relativistic methods, i.e., 2- or 1-component methods which exactly reproduce the one-electron energies of the original 4-component Dirac method, have established a standard for reliable relativistic quantum chemical calculations targeting medium- and large-sized molecules. Their development was initiated and facilitated in the late 1990s by Dyall's development of the normalized elimination of the small component (NESC). Dyall's work has fostered the conversion of NESC and related (later developed) methods into routinely used, multipurpose Dirac-exact methods by which energies, first-order, and second-order properties can be calculated at computational costs, which are only slightly higher than those of nonrelativistic methods. This review summarizes the development of a generally applicable 1-component NESC algorithm leading to the calculation of reliable energies, geometries, electron density distributions, electric moments, electric field gradients, hyperfine structure constants, contact densities and Mossbauer isomer shifts, nuclear quadrupole coupling constants, vibrational frequencies, infrared intensities, and static electric dipole polarizabilities. In addition, the derivation and computational possibilities of 2-component NESC methods are discussed and their use for the calculation of spin-orbit coupling (SOC) effects in connection with spin-orbit splittings and SOC-corrected energies are demonstrated. The impact of scalar relativistic and spin-orbit effects on molecular properties is presented. WIREs Comput Mol Sci 2014, 4:436–467. Conflict of interest: The authors have declared no conflicts of interest for this article. For further resources related to this article, please visit the WIREs website.

Journal ArticleDOI
Richard A. Lewis1, David Wood1
TL;DR: 2D QSAR models are used routinely during the process of optimization of a chemical series towards a candidate for clinical trials and will become acceptable surrogates for experimental observations as more knowledge is gained in this area.
Abstract: 2D QSAR is a powerful tool for explaining the relationships between chemical structure and experimental observations. Key elements of the method are the numerical descriptors used to translate a chemical structure into mathematical variables, the quality of the observed data and the statistical methods used to derive the relationships between the observations and the descriptors. There are some caveats to what is essentially a simple procedure: overfitting of the data, domain applicability to new structures and making good error estimates for each prediction. 2D QSAR models are used routinely during the process of optimization of a chemical series towards a candidate for clinical trials. As more knowledge is gained in this area, 2D QSARs will become acceptable surrogates for experimental observations. WIREs Comput Mol Sci 2014, 4:505–522. doi: 10.1002/wcms.1187 Conflict of interest: The authors have declared no conflicts of interest for this article. For further resources related to this article, please visit the WIREs website.

Journal ArticleDOI
TL;DR: Acevedo et al. as mentioned in this paper used a combined quantum and molecular mechanical (QM/MM) technique for modeling organic and enzymatic reactions, including substitution, decarboxylation, elimination, isomerization, and pericyclic classes.
Abstract: A recent review (Acevedo O, Jorgensen WL. Advances in quantum and molecular mechanical (QM/MM) simulations for organic and enzymatic reactions. Acc Chem Res 2010, 43:142–151) examined our use and development of a combined quantum and molecular mechanical (QM/MM) technique for modeling organic and enzymatic reactions. Advances included the pairwise-distance-directed Gaussian (PDDG)/PM3 semiempirical QM (SQM) method, computation of multidimensional potentials of mean force (PMF), incorporation of on-the-fly QM in Monte Carlo simulations, and a polynomial quadrature method for rapidly treating proton-transfer reactions. This article serves as a follow-up on our progress. Highlights include new reactions, alternative SQM methods, a polarizable OPLS force field, and novel solvent environments, e.g., ‘on water’ and room temperature ionic liquids. The methodology is strikingly accurate across a wide range of condensed-phase and antibody-catalyzed reactions including substitution, decarboxylation, elimination, isomerization, and pericyclic classes. Comparisons are made to systems treated with continuum-based solvents and ab initio or density functional theory (DFT) methods. Overall, the QM/MM methodology provides detailed characterization of reaction paths, proper configurational sampling, several advantages over implicit solvent models, and a reasonable computational cost. WIREs Comput Mol Sci 2014, 4:422–435. Conflict of interest: The authors have declared no conflicts of interest for this article. For further resources related to this article, please visit the WIREs website.

Journal ArticleDOI
TL;DR: All-electron (AE) calculations for chemical systems containing atoms of elements beyond krypton are becoming increasingly accessible and common in many fields of computational molecular science as discussed by the authors, however, general-purpose basis sets for heavy elements are rare; instead, different AE basis sets have been developed that are adapted to the requirements and peculiarities of each (approximate) relativistic treatment.
Abstract: All-electron (AE) calculations for chemical systems containing atoms of elements beyond krypton are becoming increasingly accessible and common in many fields of computational molecular science. The type, the size, and the internal construction of AE basis sets for heavy elements depend critically on the level of quantum chemical theory and, most importantly, on the way relativistic effects are treated. For this reason, general-purpose basis sets for heavy elements are rare; instead, different AE basis sets have been developed that are adapted to the requirements and peculiarities of each (approximate) relativistic treatment. Ranging from fully relativistic four-component approaches to more popular scalar relativistic approximations, today there exist complete families of AE basis sets that can cover most research needs and can be employed in diverse applications for the proper description of various molecular and atomic properties including electronic structure, chemical reactivity, and a wide range of spectroscopic parameters. For further resources related to this article, please visit the WIREs website.

Journal ArticleDOI
TL;DR: The agreement between low frequency normal modes and large conformation changes is stimulating the study of anharmonicity in protein dynamics, probably one of the most interesting direction of development in ENMs.
Abstract: Elastic network models ENMs allow to analytically predict the equilibrium dynamics of proteins without the need of lengthy simulations and force fields, and they depend on a small number of parameters and choices. Despite they are valid only for small fluctuations from the mean native structure, it was observed that large functional conformation changes are well described by a small number of low frequency normal modes. This observation has greatly stimulated the application of ENMs for studying the functional dynamics of proteins, and it is prompting the question whether this functional dynamics is a target of natural selection. From a physical point of view, the agreement between low frequency normal modes and large conformation changes is stimulating the study of anharmonicity in protein dynamics, probably one of the most interesting direction of development in ENMs. ENMs have many applications, of which we will review four general types: (1) the efficient sampling of native conformation space, with applications to molecular replacement in X-ray spectroscopy, cryo electro-miscroscopy, docking and homology modeling; (2) the prediction of paths of conformation change between two known end states; (3) the comparison of the dynamics of evolutionarily related proteins; (4) the prediction of dynamical couplings that allow the allosteric regulation of the active site from a distant control regions, with possible applications in the development of allosteric drugs. These goals have important biotechnological applications that are driving more and more attention on the analytical study of protein dynamics through ENMs. WIREs Comput Mol Sci 2014, 4:488–503. Conflict of interest: The author has declared no conflicts of interest for this article. For further resources related to this article, please visit the WIREs website.

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TL;DR: In this article, the authors address some of the more common coarse-grained (CG) techniques presented in the literature for the modeling of polymeric materials at different length scales.
Abstract: Polymers are multiscale systems by construction. They are formed by several monomeric units connected by covalent bonds whose chemical nature defines the rigidity of the chain. The interconnection between the monomeric units determines the interdependence of the motion of the different chain segments and the intrinsic multiscale nature of polymeric materials. This characteristic is reflected on the different modeling techniques that can be used to simulate polymeric materials. Because of the large conformational space that needs to be sampled when simulating polymers, coarse-grained (CG) models are commonly used and depending on which part of the system free energy (enthalpy, entropy, or both) is relevant for the properties of interest, the appropriate modeling techniques should be used. Each model is characterized by advantages and limitations that can have a great impact on the quality of the results obtained. In this overview, we address some of the more common CG techniques presented in the literature for the modeling of polymeric materials at different length scales. WIREs Comput Mol Sci 2014, 4:62–70. doi: 10.1002/wcms.1149 The authors have declared no conflicts of interest in relation to this article. For further resources related to this article, please visit the WIREs website.

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TL;DR: In this article, the 1,4-didehy-drobenzene (p-benzyne) biradical has been discussed and the energetics of this reaction and the related Schreiner-Pascal reaction as well as that of the Myers-Saito and Schmittel reactions of enyne-allenes are discussed on the basis of quantum chemical and available experimental results.
Abstract: Enediynes undergo a Bergman cyclization reaction to form the labile 1,4-didehy-drobenzene (p-benzyne) biradical. The energetics of this reaction and the related Schreiner–Pascal reaction as well as that of the Myers–Saito and Schmittel reactions of enyne-allenes are discussed on the basis of a variety of quantum chemical and available experimental results. The computational investigation of enediynes has been beneficial for both experimentalists and theoreticians because it has led to new synthetic challenges and new computational methodologies. The accurate description of biradicals has been one of the results of this mutual fertilization. Other results have been the computer-assisted drug design of new antitumor antibiotics based on the biological activity of natural enediynes, the investigation of hetero- and metallo-enediynes, the use of enediynes in chemical synthesis and materials science, or an understanding of catalyzed enediyne reactions. For further resources related to this article, please visit the WIREs website.

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TL;DR: The current view about the origin of enzymatic catalysis based on molecular simulations and its use in the design of new enzymes is illustrated.
Abstract: Theoretical and computational tools can provide a detailed knowledge of the mode of action of enzymes. This knowledge can be systematized to be used as a guide for the design of new biocatalysts for industrial purposes. In this article, we illustrate the current view about the origin of enzymatic catalysis based on molecular simulations and its use in the design of new enzymes. Transition-state stabilization in a preorganized active site seems to be the major source of catalysis, although some degree of protein flexibility is needed to reach the maximum catalytic efficiency. Development of a new enzyme must then consider the inclusion of TS stabilizing interactions either in a preexisting enzymatic structure (enzymatic redesign) or in a completely new designed enzyme (de novo design). However, the lack of a detailed understanding of the link between sequence, structure, flexibility, and function still prevents the complete success of these strategies. WIREs Comput Mol Sci 2014, 4:407–421. The authors have declared no conflicts of interest in relation to this article. For further resources related to this article, please visit the WIREs website.

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TL;DR: Clustering techniques, such as coclustering or self‐organizing trees, commonly found in bioinformatics, are beginning to find chemoinformatic application uses and new validation techniques have been introduced in the chemoinformatics literature that now allow for both a better understanding of the clustering results and help point to methods of greater efficacy.
Abstract: Chemoinformatics applications of cluster analysis over the past 35 years include chemical diversity for compound acquisition, analysis of HTS results for lead discovery, 2D and 3D chemical similarity searching for virtual screening, and hypothesis generation for lead hopping using molecular shape and pharmacophore descriptors. These applications still provide the majority of cluster analysis usage, but the advent of greater and greater computational resources has allowed researchers to tackle applications of ever increasing scale and complexity. In the past few years, a far broader array of clustering methods is now used—some entirely new, some common to other disciplines, and others modified to specific chemoinformatic applications. The chemoinformatic applications have also broadened to include greater biological information more commonly associated with bioinformatics. Indeed, clustering techniques, such as coclustering or self-organizing trees, commonly found in bioinformatics, are beginning to find chemoinformatic application uses. Issues such as visualization and validation of clustering results continue to present challenging problems, especially given that the scale of many problems now attempted has increased enormously. Some new validation techniques have been introduced in the chemoinformatics literature that now allow for both a better understanding of the clustering results and help point to methods of greater efficacy. Effective validation and visualization of clustering results of large data sets has proven to be more problematic. WIREs Comput Mol Sci 2014, 4:34–48. doi: 10.1002/wcms.1152 The authors have declared no conflicts of interest in relation to this article. For further resources related to this article, please visit the WIREs website.